Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …

The field of deep learning has seen significant advancement in recent years. However,
much of the existing work has been focused on real-valued numbers. Recent work has …

Recurrent neural networks (RNNs) are powerful architectures to model sequential data, due
to their capability to learn short and long-term dependencies between the basic elements of …

Recently, the connectionist temporal classification (CTC) model coupled with recurrent
(RNN) or convolutional neural networks (CNN), made it easier to train speech recognition …

Sessions or unique visitors is the number of visitors from one IP who accessed a journal
portal for the first time in a certain period of time. The large number of unique daily average …

Learning from data in the quaternion domain enables us to exploit internal dependencies of
4D signals and treating them as a single entity. One of the models that perfectly suits with …

This research uses Backpropagation Algorithm, Conjugate Gradient Fletcher-Reeves
(CGFR) and Resilient. The purpose of this research is to see how much iteration and …

The generation efficiency of thermoelectric generation system is relatively low, thus how
maximize its power production is of great importance. This paper designs a novel greedy …

This research uses Backpropagation Algorithm, Conjugate Gradient Fletcher-Reeves
(CGFR) and Resilient. The purpose of this research is to see how much iteration and …

This paper presents a randomized quaternion singular value decomposition (QSVD)
algorithm for low-rank matrix approximation problems, which are widely used in color face …